Data Science, Machine Learning & AI Intern

Fullsteam

1d•Remote

About The Position

It's fun to work in a company where people truly BELIEVE in what they're doing! Fullsteam is a leading provider of vertical software and embedded payments technology dedicated to helping businesses flourish by providing their customers with seamless experiences. With a dynamic and growing team of over 1,900 employees, we are committed to driving innovation and delivering best-in-class software and payment solutions that empower small and medium-sized businesses across numerous industries. Our purpose is to help our customers grow their businesses and delight their customers. Join us and be a part of a forward-thinking company that values growth, excellence, and the success of our clients. Data Science, Machine Learning & AI Intern – PIC Business Systems Business Unit Overview: PIC Business Systems is the leading provider of web-based ERP software solutions for the window covering manufacturing industry, commanding over 50% market share with a perfect implementation track record spanning 35+ years. Our flagship product, e-PIC One Enterprise, serves industry leaders including Hunter Douglas, Budget Blinds (800+ franchises via HFC), and Springs Window Fashions. PIC was acquired by Fullsteam in January 2025 and operates within the Home ERP group, bringing enterprise-grade capabilities to a stable, profitable business generating approximately $10.8M in annual revenue. PIC is at the forefront of AI adoption within Fullsteam, having deployed Claude Code across all 14 engineers (achieving a documented 33:1 ROI) and built PICasso—a custom AI-powered Support Assistant with 40+ tools built on Strands Agents SDK and FastMCP, deployed on AWS ECS Fargate and leveraging AWS Bedrock for multi-model agent orchestration. The team of 25+ employees spans engineering, support, implementation, and operations, operating in a fully remote environment with a culture defined by four core values: Win Together, Embrace Change, Don’t Report the News, and Own the Outcome. Job Summary: The Data Science, Machine Learning & AI Intern will be PIC’s first dedicated data science and AI agent development role, responsible for developing predictive models, building analytics pipelines, creating and enhancing AI agents on AWS Bedrock, and embedding ML-driven insights into PIC’s products and operations. Reporting directly to the President, this intern will have access to rich multi-tenant ERP datasets spanning hundreds of window covering manufacturers and hands-on involvement with PICasso’s production AI agent infrastructure, providing a unique opportunity to work across the full spectrum of applied AI—from statistical modeling to autonomous agent development—in an industry-specific SaaS context. This role is ideal for a graduate student or advanced undergraduate in statistics, data science, machine learning, or a related quantitative field who wants hands-on experience building production ML systems and AI agents in a real business environment. The intern will contribute to PIC’s AI strategy while gaining exposure to enterprise SaaS operations, manufacturing domain expertise, and cloud infrastructure on AWS.

Requirements

Strong foundation in statistics, probability, and machine learning algorithms (regression, classification, clustering, time series forecasting)
Proficiency in Python with data science libraries (pandas, NumPy, scikit-learn, TensorFlow/PyTorch)
Experience with SQL and relational databases; ability to write complex analytical queries against large datasets
Familiarity with LLMs, prompt engineering, and AI agent frameworks (experience with AWS Bedrock, LangChain, or similar a plus)
Familiarity with data visualization tools and libraries (Matplotlib, Seaborn, Plotly, or similar)
Understanding of ETL pipeline design and data engineering fundamentals
Strong analytical thinking with the ability to translate business problems into data science and AI solutions
Excellent written and verbal communication skills; ability to explain technical findings to non-technical stakeholders
Self-motivated with the ability to work independently in a remote environment
Intellectual curiosity and willingness to learn domain-specific knowledge in manufacturing and ERP systems
Currently pursuing or recently completed a Master’s degree in Statistics, Data Science, Computer Science, Machine Learning, Mathematics, or a related quantitative field
Coursework or project experience in machine learning, statistical modeling, or predictive analytics
Proficiency in Python and SQL
Experience with at least one ML framework (scikit-learn, TensorFlow, PyTorch, or similar)
Portfolio or academic projects demonstrating applied data science or AI work (Kaggle competitions, research projects, agent prototypes, or capstone work acceptable)

Nice To Haves

Experience with AWS services (Bedrock, SageMaker, Glue, Athena, ECS, or similar)
Hands-on experience building or working with LLM-based agents, tool-use patterns, or multi-agent architectures
Graduate-level coursework or research in machine learning, NLP, or time series analysis
Familiarity with MySQL/Aurora MySQL in production environments
Exposure to multi-tenant SaaS data architectures
Experience with version control (Git/GitHub) and collaborative development workflows
Experience with MCP (Model Context Protocol), FastMCP, or similar agent tooling frameworks
Knowledge of manufacturing, supply chain, or ERP domains

Responsibilities

Build, maintain, and enhance AI agents using AWS Bedrock, including designing agent tool schemas, implementing post-condition validation, and optimizing agent performance across PICasso’s multi-agent architecture
Develop, test, and deploy new PICasso agent capabilities using Strands Agents SDK and FastMCP, contributing to the 40+ tool ecosystem that powers customer support operations
Design, train, and validate machine learning models for customer attrition prediction, leveraging ERP usage patterns, support ticket history, billing data, and engagement signals across PIC’s multi-tenant MySQL databases
Build supply and demand forecasting models for window covering manufacturing, incorporating seasonality, material pricing trends, and historical order data to improve production planning accuracy
Develop and maintain ETL data pipelines to extract, transform, and load data from Aurora MySQL multi-tenant databases into analytics-ready formats
Create interactive customer analytics dashboards and PicRite reports that surface actionable insights for account management, customer success, and executive leadership
Integrate ML-driven pricing validation logic to detect anomalies and optimize franchise pricing across large dealer networks (e.g., Budget Blinds)
Conduct exploratory data analysis to identify patterns, trends, and opportunities within PIC’s extensive ERP dataset
Participate in agent quality audits (review_low_scores) and contribute to reducing hallucination rates and improving agent accuracy
Document all models, agents, assumptions, data sources, and methodologies; present findings to engineering leadership and stakeholders
Collaborate with engineering, support, and implementation teams to understand business context and ensure model and agent relevance